Today's vehicles are combined with IT technology to provide various functions. In order to enhance a driving stability of a vehicle and to improve convenience of users, various types of advanced driver-assistance system (ADAS) are being developed.
Herein, the ADAS is implemented by using advanced sensing devices and intelligent imaging devices to provide various information for autonomous driving, and it includes a pedestrian & car recognition system, a road surface recognition system, a lane recognition system, a crash prevention system, a lane departure warning system, etc.
However, these conventional ADASs use many various sensors and cameras for recognizing a driving environment of the vehicle and a driver's status, resulting in increasing the cost.
Further, in the conventional ADASs, the sensors and the cameras should be installed at optimal positions for acquiring relevant information. But if errors in position and sensing direction occur, then accurate information cannot be obtained and, accordingly, the accurate information cannot be provided for assisting the driver.